August 20, 2012

Clever Pacman

Nicole Alicia Rossini, Christian Quadri, N. Alberto Borghese. “Clever Pac-man”. ┬áNeural Nets WIRN11. ┬ádoi:10.3233/978-1-60750-972-1-11

In this paper we show how combining fuzzy sets and reinforcement learning a winning agent can be created for the popular Pac-man game. Key elements are the classification of the state into a few fuzzy classes that makes the problem manageable. Pac-man policy is defined in terms of fuzzy actions that are defuzzified to produce the actual Pac-man move. A few heuristics allow making the Pac-man strategy very similar to the Human one. Ghosts agents, on their side, are endowed also with fuzzy behavior inspired by original design strategy. Performance of this Pac-man is shown to be superior to those of other AI-based Pac-man described in the literature.

Developed in java for the Artificial Intelligence exam with Christian Quadri.

Full documentation CleverPacman (italian)

User Manual CleverPacman(italian)

Code can be downloaded here.